Ipsilesional Mu Rhythm Desynchronization and Changes in Motor Behavior Following Post Stroke BCI Intervention for Motor Rehabilitation

I can't see how any of this helps. I don't see where an objective damage starting point is measured so there is no way to know exactly who might be helped by this. 

Ipsilesional Mu Rhythm Desynchronization and Changes in Motor Behavior Following Post Stroke BCI Intervention for Motor Rehabilitation

Alexander B. Remsik^1,2,3*†, Leroy Williams Jr.^1,4,5†, Klevest Gjini^1,6, Keith Dodd^1,7, Jaclyn Thoma^1,8, Tyler Jacobson^1,8, Matt Walczak¹, Matthew McMillan^1,7, Shruti Rajan^1,9, Brittany M. Young^1,3,8,10,11, Zack Nigogosyan¹, Hemali Advani¹, Rosaleena Mohanty^1,12, Neelima Tellapragada¹, Janerra Allen¹³, Mohsen Mazrooyisebdani¹, Leo M. Walton^7,8, Peter L. E. van Kan², Theresa J. Kang^1,6, Justin A. Sattin⁸, Veena A. Nair¹, Dorothy Farrar Edwards², Justin C. Williams^7,14 and Vivek Prabhakaran^{1,6,8,9,11,15}

• ¹Department of Radiology, University of Wisconsin–Madison, Madison, WI, United States
• ²Department of Kinesiology, University of Wisconsin–Madison, Madison, WI, United States
• ³Institute for Clinical and Translational Research, University of Wisconsin–Madison, Madison, WI, United States
• ⁴Department of Educational Psychology, University of Wisconsin–Madison, Madison, WI, United States
• ⁵Center for Women’s Health Research, University of Wisconsin–Madison, Madison, WI, United States
• ⁶Department of Neurology, University of Wisconsin–Madison, Madison, WI, United States
• ⁷Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States
• ⁸Neuroscience Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States
• ⁹Department of Psychology, University of Wisconsin–Madison, Madison, WI, United States
• ¹⁰Clinical Neuroengineering Training Program, University of Wisconsin–Madison, Madison, WI, United States
• ¹¹Medical Scientist Training Program, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States
• ¹²Department of Electrical and Computer Engineering, University of Wisconsin–Madison, Madison, WI, United States
• ¹³Department of Materials Science and Engineering, University of Wisconsin–Madison, Madison, WI, United States
• ¹⁴Department of Neurological Surgery, University of Wisconsin–Madison, Madison, WI, United States
• ¹⁵Department of Psychiatry, University of Wisconsin–Madison, Madison, WI, United States

Loss of motor function is a common deficit following stroke insult and often manifests as persistent upper extremity (UE) disability which can affect a survivor’s ability to participate in activities of daily living. Recent research suggests the use of brain–computer interface (BCI) devices might improve UE function in stroke survivors at various times since stroke. This randomized crossover-controlled trial examines whether intervention with this BCI device design attenuates the effects of hemiparesis, encourages reorganization of motor related brain signals (EEG measured sensorimotor rhythm desynchronization), and improves movement, as measured by the Action Research Arm Test (ARAT). A sample of 21 stroke survivors, presenting with varied times since stroke and levels of UE impairment, received a maximum of 18–30 h of intervention with a novel electroencephalogram-based BCI-driven functional electrical stimulator (EEG-BCI-FES) device. Driven by spectral power recordings from contralateral EEG electrodes during cued attempted grasping of the hand, the user’s input to the EEG-BCI-FES device modulates horizontal movement of a virtual cursor and also facilitates concurrent stimulation of the impaired UE. Outcome measures of function and capacity were assessed at baseline, mid-therapy, and at completion of therapy while EEG was recorded only during intervention sessions. A significant increase in r-squared values [reflecting Mu rhythm (8–12 Hz) desynchronization as the result of attempted movements of the impaired hand] presented post-therapy compared to baseline. These findings suggest that intervention corresponds with greater desynchronization of Mu rhythm in the ipsilesional hemisphere during attempted movements of the impaired hand and this change is related to changes in behavior as a result of the intervention. BCI intervention may be an effective way of addressing the recovery of a stroke impaired UE and studying neuromechanical coupling with motor outputs.
Clinical Trial Registration: ClinicalTrials.gov, identifier NCT02098265.

Introduction

Stroke

Stroke is a leading cause of acquired adult long-term disability in the United States (Benjamin et al., 2017) and occurs when blood supply to the brain is compromised, leading to functional deficits that may affect activities of daily living (ADLs). Approximately 85% of patients who suffer and survive a new or recurrent stroke in the United States each year require rehabilitation (Yang et al., 2017). Six months post-stroke, nearly 50% of survivors have some residual motor deficits (Benjamin et al., 2017). By 2050, stroke burden on the United States economy will approach $2.2 trillion (Benjamin et al., 2017). Despite advances in acute stroke care, the estimated direct and indirect costs of stroke continue to escalate and are disproportionally associated with long-term care and rehabilitation (Benjamin et al., 2017). Current standard of care seems insufficiently developed to treat long-term motor deficits, potentially further burdening patients as untreated motor impairment can lead to deconditioning and underutilization of the affected upper extremity (UE), a consequence deemed, learned non-use (LNU) (Schaechter, 2004).

Customary Care and the Opportunities for Improvement

Several rehabilitation techniques are traditionally used for stroke recovery including conventional physical-occupational-speech therapies, provided in acute care settings as well as newer motor therapies such as constraint-induced movement therapy (CIMT), robot-aided therapy, transcranial direct current stimulation (tDCS), transcranial magnetic stimulation (TMS), and virtual reality (VR) (Kollen et al., 2006; Lindenberg et al., 2010; Fleet et al., 2014; Young et al., 2014a,b,c; Laver et al., 2015; Song et al., 2015; Babaiasl et al., 2016; Smith and Stinear, 2016). Importantly, a much different level of evidence exists for CIMT and traditional therapies than experimental therapies such as tDCS and VR-based approaches. Existing pharmacological treatments, Botox injections for example, and traditional physical therapy methods primarily serve to treat symptoms associated with stroke (Benjamin et al., 2017) and may not focus on bringing about basic changes to the underlying impaired brain function associated with relevant post-stroke pathologies. Patients with UE motor impairment traditionally receive rehabilitation regimens that involve passive, repetitive movement of the impaired limb without directly linking brain activity to these movements (Dromerick et al., 2009). Whereas passive movement repetition can be an effective rehabilitation strategy, recovery can be slow, and suboptimal. In contrast, linking brain activity to movement is important for motor skill learning (e.g., walking, running, throwing, writing, etc.) and the formation of central to peripheral connections. Leveraging this innate and robust motor learning circuitry, harnessing brain plasticity (Thakor, 2013), may be the next step toward improve patient outcomes.

Motor Recovery

Research suggests that motor recovery post-stroke, similar to motor learning, requires specific internal and external environmental conditions (Power et al., 2011; Wenger et al., 2017). For example, lesion load is a limiting factor as sufficient existing neural-architecture is needed for motor recovery to occur (Power et al., 2011). Recovery likely manifests either by the return of function to surviving neural architecture, or via neural reorganization and neural network remapping of proximal (i.e., near-by) neural architecture (Gazzaniga, 2005; Jones, 2017). Perhaps such processes may even be related. If neuroplasticity in the motor system, though likely attenuated by age, is continuous (Gazzaniga, 2005) over the life course (Power et al., 2011; Wenger et al., 2017), long-studied learning theories such as Hebbian plasticity and classical conditioning might be better integrated in treatment designs to aid recovery of stroke impaired UE motor capacities (Power et al., 2011; Remsik et al., 2016). The incorporation of neurorehabilitation techniques has yielded operational clinical therapies and devices (Pfurtscheller et al., 1997, 2005; Neuper and Pfurtscheller, 2001; Pineda, 2005; Felton et al., 2007; Schalk et al., 2008; Power et al., 2011; Kuiken et al., 2013; Young et al., 2014a; Wenger et al., 2017). As a number of existing approaches suffer from issues of high cost, passive movement repetition, large equipment, personnel and time constraints it is crucial efforts are made to pursue more expedient and efficacious means of rehabilitation, improve our quality of care, and better serve our survivors.

Sensorimotor Rhythms

Human brain rhythms associated with motor output, sensorimotor rhythms (SMRs), are recorded superficial to the motor and somatosensory cortical strip of the brain (electrode sites C3 and C4) and originate according to homuncular organization (Pfurtscheller et al., 1997; Birbaumer et al., 2006). At the motor cortical strip (generally, Brodmann areas 3–6), each brain hemisphere desynchronizes with imagined, attempted, and also preparation of movement. This phenomenon is known as event-related desynchronization (ERD). Specific frequency bands have been associated with specific aspects of event-related motor behaviors (Pfurtscheller et al., 1997, 2005; Felton et al., 2007; Schalk et al., 2008; Song et al., 2014; Young et al., 2014b). In normal effortful movement, Mu rhythms of the contralateral cortex are desynchronized and attenuated (ERD) as movements are planned and executed (Pfurtscheller et al., 1997). This is followed by an increased presence of Beta rhythm ERD in the contralateral motor cortex which is associated with the later stages of motor command output and control (Pineda, 2005). After the completion, or at the cessation of movement, the SMRs in Mu and Beta frequency bands synchronize (ERS). ERD and ERS were key elements in the development and use of early BCIs for the rehabilitation of motor functions (Pfurtscheller et al., 1997, 2005; Nam et al., 2011). The early designs confirmed that ERD or ERS in specific spatial areas and neural networks (e.g., thalamocortical networks, frontoparietal networks) associated with a task or triggered events can be utilized to control a device or output command (Pfurtscheller et al., 1997; Neuper and Pfurtscheller, 2001).

Mu and Beta sensorimotor rhythms (SMRs) in human subjects are recorded exclusively over sensorimotor areas at frequencies of about 10–20 Hz (Pfurtscheller et al., 1997; Birbaumer et al., 2006). Two basic strategies in SMR-based control have been introduced for motor rehabilitation in stroke patients: motor imagery (Wolpaw et al., 1991; Ortner et al., 2012; Irimia et al., 2016) and attempted movement-based approaches (Wolpaw et al., 1991; Schalk et al., 2004; Young et al., 2014a,b,c). Either approach utilizes essentially overlapping neural architecture to provide input signals (electrophysiological recordings by the EEG cap) to the BCI. The authors of this study designed the protocol to utilize attempted hand movements during the intervention according to the logic that a motor therapy intended to restore volitional motor function of the affected UE should utilize voluntary attempted movements of that impaired hand in a continuous effort to improve the participant’s UE capacity and performance.

Brain–Computer Interface (BCI) and Electroencephalography for Assistive Design

Noninvasive brain–computer interfaces (BCIs), which utilize ancillary adjuvant peripheral devices and electrical muscle stimulation, as well as invasive BCI approaches with electrodes implanted in the skull, have been introduced (Wolpaw et al., 1991; Leuthardt et al., 2004; Schalk et al., 2004, 2008; McFarland et al., 2006; Felton et al., 2007) as contemporary intervention and rehabilitation techniques following neural disease or trauma, such as stroke. Devices similar to what was utilized in this research are controlled by input signals generated by scalp electroencephalographic (EEG) recordings from electrodes superficial to the sensorimotor cortices. EEG signals associated with various components of voluntary movement are identified and translated into a device command or specified output (Pfurtscheller et al., 1997, 2005; Felton et al., 2007; Schalk et al., 2008; Wilson et al., 2012), like activation of an FES pad (Song et al., 2014; Young et al., 2014a,b). BCIs can monitoring volitional modulation of electrical brain rhythms and execute an augmentative, facilitative, or rehabilitative command in the presence or absence of such signals.

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